You are using transfer learning to train an image classifier based on a pre-trained EfficientNet model. Your training dataset has 20,000 images. You plan to retrain the model once per day. You need to

The correct answer is D. An AI Platform Training job using a custom scale tier with 4 V100 GPUs and Cloud Storage. The pre-trained EfficientNet model can be easily loaded from Cloud Storage, which eliminates the need for local storage or an NFS server. Using AI Platform Training allows for the automatic scaling of resources based on the size of the dataset, which can save costs compared to us

Submitted by ngozi_ng· Apr 18, 2026ML pipeline operationalization

Question

You are using transfer learning to train an image classifier based on a pre-trained EfficientNet model. Your training dataset has 20,000 images. You plan to retrain the model once per day. You need to minimize the cost of infrastructure. What platform components and configuration environment should you use?

Options

AA Deep Learning VM with 4 V100 GPUs and local storage.
BA Deep Learning VM with 4 V100 GPUs and Cloud Storage.
CA Google Kubernetes Engine cluster with a V100 GPU Node Pool and an NFS Server
DAn AI Platform Training job using a custom scale tier with 4 V100 GPUs and Cloud Storage

How the community answered

(32 responses)

A
3% (1)
B
3% (1)
C
13% (4)
D
81% (26)

Explanation

The pre-trained EfficientNet model can be easily loaded from Cloud Storage, which eliminates the need for local storage or an NFS server. Using AI Platform Training allows for the automatic scaling of resources based on the size of the dataset, which can save costs compared to using a fixed-size VM or node pool. Additionally, the ability to use custom scale tiers allows for fine-tuning of resource allocation to match the specific needs of the training job.

Topics

#Cloud ML Platform#Managed Services#Cost Optimization#GPU Training

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